缅北禁地

Introduction:

I earned my master’s in biomedical engineering with neurotechnology from Imperial College, London, as a Whitaker International Fellow, and my doctorate in neuroscience from the University of Southern California, under the supervision of . My thesis focused on predicting the progression of human chronic pain symptoms from resting-state fMRI connectivity utilising machine learning techniques. I subsequently completed a postdoctoral position in early childhood development with  (Cedars-Sinai Medical Center, USA). I am currently a postdoctoral research associate at 缅北禁地, UK, investigating co-occurring autism and epilepsy with Peter Taylor. I have a longstanding interest in elucidating the relationships between brain function and behavioural markers in health and disease, particularly in neurodevelopment.

Previous Positions:

• 2020-2023: Postdoctoral Scientist at Biomedical Imaging Research Institute (BIRI), Cedars-Sinai Medical Center, USA

Qualifications:

• 2020: Ph.D. in Neuroscience, University of Southern California, USA
• 2013: MSc in Biomedical Engineering w. Neurotechnology, Imperial College London, UK
• 2012: BSc in Biomedical Engineering, University of California Davis, USA 

Areas of expertise:

Neuroimaging, machine learning, advanced statistics, and neuromodulation. Research that addresses basic neuroscience questions and its translation to clinical applications in health and disease, and neurodevelopment.

Current research:

My current research focuses on investigating neuroimaging targets in ASD and epilepsy co-occurrence. I utilize data-driven, normative modelling and advanced statistical approaches to detect brain features relating to co-occurring phenotypical traits. My expertise is in the application of advanced statistics to large multi-site neuroimaging datasets to study heterogeneity in specific patient subpopulations, identifying functional neural signatures relative to symptom change and associations with behavioural outcomes. I leverage functional and structural MRI to study these populations. I have previously identified sex differences in resting-state (rs) fMRI brain connectivity data during postnatal development with behavioural measures of language and executive function. In addition, I have worked with large rs-fMRI datasets from multi-site collaborations to identify biomarkers in neurophysiological data that predicted longitudinal symptom change. Ultimately, by characterising brain features in health and disease, the goal of my research is to significantly improve early detection, critical for strategic intervention and enhanced quality of life in vulnerable populations.  

Research Interests:

• Co-occurring neurodevelopment conditions
• Structural and functional mechanics underlying human brain development
• Early development of sex differences and brain-behavior relationships
• Neuromodulation as a therapeutic intervention

Skills:

• Data analysis, advanced statistics and machine learning
• MRI image processing and analysis packages: FSL, AFNI, FreeSurfer
• Programming languages: MATLAB, SAS, and Python
• Transcranial Magnetic Stimulation (TMS)

Publications:

Pre-prints: 

• Fenske, S., Liu, J., Chen, H., Diniz, M., Stephens R., Cornea, E., Gilmore, J., Gao, W. (2023). Sex differences in brain-behavior relationships during infancy. Preprint. https://doi.org/10.1101/2024.01.31.578147

Journals:

• Fenske, S., Liu, J., Chen, H., Stephens, R., Cornea, E., Gilmore, J., Gao, W. (2023). Sex differences in resting state functional connectivity across the first two years of life. Developmental Cognitive Neuroscience. https://doi.org/10.1016/j.dcn.2023.101235 
• Fenske, S., Bierer, D., Chelimsky, G., Chelimsky, T., Kutch, J.J. (2020). Sensitivity of functional connectivity to periaqueductal gray localization with implications for identifying disease-related changes in chronic visceral pain: A MAPP Research Network Neuroimaging Study. Neuroimage - Clinical. https://doi.org/10.1016/j.nicl.2020.102443 
• Yani, M., Fenske, S., Rodriguez, L., Kutch, J.J. (2022). Cortical Neuromodulation of Pelvic Floor Muscle Tone: A Proof-of-Concept Study. Neuromodulation. 
• Yani, M., Fenske, S., Rodriguez, L., Kutch, J.J. (2019). Motor cortical neuromodulation of pelvic floor muscle tone: potential implications for the treatment of urologic conditions. Neurourology and Urodynamics. 
• Kutch, J.J., Labus, J.S., Harris, R.E., Martucci, K.T., Farmer, M.A., Fenske, S., Fling, C., Ichesco, E., Peltier, S., Petre, B., Guo, W., Hou, X., Stephens, A.J., Mullins, C., Clauw, D.J., Mackey, S.C., Apkarian, A.V., Landis, J.R., Mayer, E.A., MAPP Research Network. (2017). Resting-state functional connectivity predicts longitudinal pain symptom change in urologic chronic pelvic pain syndrome: a MAPP Network study. PAIN. 158. 1. 10.1097/j.pain.0000000000000886.
• Thomik, A.A.C., Fenske, S., Faisal, A.A. (2015). Towards sparse coding of natural movements for neuroprosthetics and brain-machine interfaces. 7th International IEEE/EMBS Conference on Neural Engineering (NER), pp. 938-941. 
• Goodfellow, A.M., Mohr, R., Purewal, S., Fenske, S., Hawkins, D., Casazza, G.A. (2012). ACL Injury Risk Reduction Training Intervention in Female High School Soccer Players. Medicine and science in sports and exercise, Vol.44(5S), pp.266-266.

• 2021-2022: Artificial Intelligence and Advanced Imaging Analysis, MRM 33, Cedars-Sinai Graduate School of Biomedical Sciences
• 2016-2020: Teaching Assistant, University of Southern California.
• Fundamentals of Neuroscience, Physical Therapy 569
• MATLAB Bootcamp